Impact of Express Delivery Industry’s Development on Transportation Sector’s Carbon Emissions: An Empirical Analysis from China

In recent years, China’s express delivery industry has developed rapidly. According to a rough estimate in this paper, carbon emissions caused by express parcel transportation in China account for 1/7 of the transportation sector’s carbon emissions. However, considering the possibility of a scale effect, it is unclear whether the express delivery industry’s development will inevitably lead to more carbon emissions. Therefore, this paper uses the panel data of 30 Chinese provinces from 2008 to 2017 to explore the complex relationship between the express delivery industry’s development and the transportation sector’s carbon emissions, and also conducts regional heterogeneity analysis. The main findings are as follows: (1) There is a significant U-shaped relationship between per capita express delivery amounts and the transportation sector’s CO2 emissions, especially in the Central region. (2) At the national level, the number of per capita postal outlets significantly promotes the transportation sector’s CO2 emissions. (3) The impact caused by the number of per capita postal workers varies regionally. Increasing postal worker numbers in the Western region can significantly reduce carbon emissions, while the result in the Central region is the opposite. (4) The Express Comprehensive Development Index (ECDI) has a significant U-shaped effect on the transportation sector’s carbon emissions at the national and sub-regional level.

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Economic Development, CO2 Emissions and Energy Use Nexus-Evidence from the Danube Region Countries

Energies ◽

10.3390/en14113165 ◽

2021 ◽

Vol 14 (11) ◽

pp. 3165

Author(s):

Eva Litavcová ◽

Jana Chovancová

Keyword(s):

Economic Growth ◽

Energy Consumption ◽

Co2 Emissions ◽

Carbon Emissions ◽

Bounds Testing ◽

Mutual Cooperation ◽

Long Run ◽

Short Run ◽

Danube Region ◽

The Impact

The aim of this study is to examine the empirical cointegration, long-run and short-run dynamics and causal relationships between carbon emissions, energy consumption and economic growth in 14 Danube region countries over the period of 1990–2019. The autoregressive distributed lag (ARDL) bounds testing methodology was applied for each of the examined variables as a dependent variable. Limited by the length of the time series, we excluded two countries from the analysis and obtained valid results for the others for 26 of 36 ARDL models. The ARDL bounds reliably confirmed long-run cointegration between carbon emissions, energy consumption and economic growth in Austria, Czechia, Slovakia, and Slovenia. Economic growth and energy consumption have a significant impact on carbon emissions in the long-run in all of these four countries; in the short-run, the impact of economic growth is significant in Austria. Likewise, when examining cointegration between energy consumption, carbon emissions, and economic growth in the short-run, a significant contribution of CO2 emissions on energy consumptions for seven countries was found as a result of nine valid models. The results contribute to the information base essential for making responsible and informed decisions by policymakers and other stakeholders in individual countries. Moreover, they can serve as a platform for mutual cooperation and cohesion among countries in this region.

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Analyzing the Renewable Energy and CO2 Emission Levels Nexus at an EU Level: A Panel Data Regression Approach

Processes ◽

10.3390/pr9010130 ◽

2021 ◽

Vol 9 (1) ◽

pp. 130

Author(s):

Mihail Busu ◽

Alexandra Catalina Nedelcu

Keyword(s):

Renewable Energy ◽

Panel Data ◽

Co2 Emissions ◽

Co2 Emission ◽

Negative Impact ◽

National Level ◽

Renewable Energy Consumption ◽

Urbanization Level ◽

Carbon Dioxide Co2 ◽

The Impact

In the past decades, carbon dioxide (CO2) emissions have become an important issue for many researchers and policy makers. The focus of scientists and experts in the area is mainly on lowering the CO2 emission levels. In this article, panel data is analyzed with an econometric model, to estimate the impact of renewable energy, biofuels, bioenergy efficiency, population, and urbanization level on CO2 emissions in European Union (EU) countries. Our results underline the fact that urbanization level has a negative impact on increasing CO2 emissions, while biofuels, bioenergy production, and renewable energy consumption have positive and direct impacts on reducing CO2 emissions. Moreover, population growth and urbanization level are negatively correlated with CO2 emission levels. The authors’ findings suggest that the public policies at the national level must encourage the consumption of renewable energy and biofuels in the EU, while population and urbanization level should come along with more restrictions on CO2 emissions.

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Effects of Kyoto Protocol on CO2 Emissions: A Five-Country Rolling Regression Analysis

Sustainability ◽

10.3390/su11030744 ◽

2019 ◽

Vol 11 (3) ◽

pp. 744

Author(s):

Chien-Ho Wang ◽

Ming-Hui Ko ◽

Wan-Jiun Chen

Keyword(s):

Co2 Emissions ◽

Kyoto Protocol ◽

Carbon Dioxide Emissions ◽

Global Financial Crisis ◽

Turning Points ◽

Developed Countries ◽

Heated Debate ◽

Per Capita ◽

Rolling Regression ◽

The Impact

The current study illustrated the time variance of turning points in the relationship between carbon emissions and income to resolve heated debate on the different responsibility to climate change with 1950–2010 data of five development diversity countries—three developed countries (Germany, Italy, and Japan) and one developing country (India) and one newly industrialized economy (Taiwan). The article also examines the impact of the crisis on emission. The time-varying patterns in the turning points on environmental Kuznets curves (EKCs) were observed by a rolling regression technique with 1950–2010 data regarding the per capita CO2 emissions caused by fossil fuel combustion and the incomes of the countries. Several empirical findings were revealed from this analysis. Per capita CO2 emissions commonly decreased with varying magnitudes in the five countries over time. The EKC hypothesis regarding the CO2 emissions is affirmed again in this study. The announcement effects associated with the Kyoto Protocol was evidenced. As indicated by the occurring GDP of the turning point, there is a strong reduction trend in the income level of the turning points right before the years of Kyoto Protocol; and this decreasing trend nearly ended as the Kyoto protocol approached its end, except in Germany, where the occurring income of the turning points continued to have a decreasing trend. Although the global financial crisis had its effects in the world, the impacts on carbon dioxide emissions vary across countries.

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Big Data Analytics Capabilities and Eco-Innovation: A Study of Energy Companies

Sustainability ◽

10.3390/su11154254 ◽

2019 ◽

Vol 11 (15) ◽

pp. 4254 ◽

Cited By ~ 3

Author(s):

Munodawafa ◽

Johl

Keyword(s):

Big Data ◽

Production Process ◽

Co2 Emissions ◽

Data Analytics ◽

Strong Predictor ◽

Big Data Analytics ◽

Cleaner Production ◽

Mitigation Strategies ◽

Per Capita ◽

The Impact

Increased greenhouse gas (GHG) emissions in the past decades have created concerns about the environment. To stymie global warming and the deterioration of the natural environment, global CO2 emissions need to reach approximately 1.3 tons per capita by 2050. However, in Malaysia, CO2 output per capita—driven by fossil fuel consumption and energy production—is expected to reach approximately 12.1 tons by the year 2020. GHG mitigation strategies are needed to address these challenges. Cleaner production, through eco-innovation, has the potential to arrest CO2 emissions and buttress sustainable development. However, the cleaner production process has been hampered by lack of complete data to support decision making. Therefore, using the resource-based view, a preliminary study consisting of energy and utility firms is undertaken to understand the impact of big data analytics towards eco-innovation. Linear regression through SPSS Version 24 reveals that big data analytics could become a strong predictor of eco-innovation. This paper concludes that information and data are key inputs, and big data technology provides firms the opportunity to obtain information, which could influence its production process—and possibly help arrest increasing CO2 emissions.

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Comparison of CO2 emissions reduction efficiency of household fuel consumption in China

Sustainability ◽

10.3390/su11040979 ◽

2019 ◽

Vol 11 (4) ◽

pp. 979 ◽

Cited By ~ 4

Author(s):

Bingjie Xu ◽

Ruoyu Zhong ◽

Yifeng Liu

Keyword(s):

Natural Gas ◽

Co2 Emissions ◽

Negative Impact ◽

National Level ◽

Energy Structure ◽

Kuznets Curve ◽

Liquefied Petroleum Gas ◽

Gas Consumption ◽

Natural Gas Consumption ◽

Per Capita

The purpose of this paper is to analyze the correlations among per capita gross domestic product (GDP), household fuel (natural gas and liquefied petroleum gas) consumption, and carbon dioxide (CO2) emissions through the environmental Kuznets curve (EKC) at the regional and national level in China using data from 2003 to 2015. The results validate the EKC assumption and show that per capita GDP is positively related to CO2 emissions; per capita natural gas consumption has a negative impact on CO2 emissions; however, per capita liquefied petroleum gas (LPG) consumption has a positive effect on CO2 emissions. Therefore, increasing natural gas consumption can effectively slow down the environmental degradation of China. Given rapid economic growth, changing the energy structure can improve the environment.

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PERTUMBUHAN PENDUDUK, INFLASI DAN KORUPSI: ANALISIS EMPIRIS ENVIRONMENTAL KUZNETS CURVE (EKC) DI KAWASAN ASEAN PERIODE 2002-2016

JURNAL DINAMIKA EKONOMI PEMBANGUNAN ◽

10.14710/jdep.1.3.71-81 ◽

2019 ◽

Vol 1 (3) ◽

pp. 71

Author(s):

Muhammad Fajri Setia Trianto ◽

Evi Yulia Purwanti

Keyword(s):

Economic Growth ◽

Population Growth ◽

Co2 Emissions ◽

Environmental Kuznets Curve ◽

Secondary Data ◽

Gdp Per Capita ◽

Environmental Damage ◽

Kuznets Curve ◽

Per Capita ◽

The Impact

The economy that continues to grow has the impact of environmental damage. This study aims to prove empirically the Environmental Kuznets Curve (EKC) hypothesis by analyzing the relationship of economic growth with environmental damage as measured by GDP per capita, and CO2 emissions. The data used are secondary data in the form of data on GDP per capita, CO2 emissions, population growth, inflation, and control of corruption in 10 countries in the ASEAN region in 2002-2016. Data analysis using the Fixed Effect model. The results show that there is a relationship between economic growth and environmental damage that forms an inverted U curve. Economic growth will initially have a positive effect on environmental damage so that at a point of economic growth negatively affects environmental damage. By adding control variables: population growth, inflation and corruption, inflation and corruption positively impact environmental damage, while population negatively affect environmental damage.

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The Impacts of Spatial Interaction on Agricultural Productivity and Average Income: A Case of Vietnam

Journal La Sociale ◽

10.37899/journal-la-sociale.v2i2.372 ◽

2021 ◽

Vol 2 (2) ◽

pp. 12-20

Author(s):

Bac Truong Cong ◽

Tran Quang Van

Keyword(s):

Spatial Interaction ◽

Panel Data Analysis ◽

National Level ◽

Agricultural Productivity ◽

Transportation Systems ◽

Living Standards ◽

Economic Policies ◽

Average Income ◽

Per Capita ◽

The Impact

Agricultural productivity plays a crucial role in sustainable development while income is one of the most critical indicators that manifest the living standards; therefore, both of these aspects have attracted much attention from the national level to the provincial level. Yet, for various reasons, the importance of regional linkages, especially spatial interaction in the analysis of agricultural productivity and the average income, is not recognized and thus ignored in economic policies. Taking Vietnam as the study area, this paper examines the impact of spatial interaction between metropolises and provinces on agricultural productivity and income per capita of provinces. In order to evaluate the impacts, this paper uses a gravity model to estimate the spatial interaction then panel data analysis is employed to interpret the influences. The data used in this study is collected from the General Statistics Office of Vietnam in the period from 2015-2018. The results show a positive correlation between spatial interaction between metropolis and provinces to provincial change, including agricultural productivity and average income. As such, stronger linkages with metropolises through improving transportation systems could enhance agricultural productivity and income in the province.

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The Impact of Urban Transportation Infrastructure on Air Quality

Sustainability ◽

10.3390/su12145626 ◽

2020 ◽

Vol 12 (14) ◽

pp. 5626 ◽

Cited By ~ 1

Author(s):

Yujing Guo ◽

Qian Zhang ◽

Kin Keung Lai ◽

Yingqin Zhang ◽

Shubin Wang ◽

...

Keyword(s):

Air Pollution ◽

Air Quality ◽

Motor Vehicle ◽

National Level ◽

Transportation Infrastructure ◽

Gdp Per Capita ◽

Infrastructure Investment ◽

Empirical Results ◽

Per Capita ◽

The Impact

While previous study has confirmed significant correlation between infrastructure construction and air quality, little is known about the nature of the relationship. In this paper, we intend to fill this gap by using the Panel Smooth Transition Regression (PSTR) model to discuss the nonlinear relationship between transportation infrastructure construction and air quality. The panel data includes 280 cities in China for the period 2000-2017. We find that the transportation infrastructure investment is positively correlated to the air quality when the GDP per capita is below RMB 7151 or the number of motor vehicle population per capita is below 37 (vehicles per 10,000 persons) where the model is in the lower regime, and that the transportation infrastructure investment is negatively correlated to the air quality when the GDP per capita is greater than RMB 7151 or the number of motor vehicle population per capita is larger than 37 (vehicles per 10,000 persons) where the model is in the upper regime. The empirical results of the three sub-samples, including eastern, western and central regions, are similar to that of the national level. Furthermore, increasing transportation infrastructure investment is conducive to improving air quality. Urban bus services, green area, population density, wind speed and rainfall are also conducive to reducing air pollution, but the role of environmental regulation is not significant. After adding the instrumental variable (urban built-up area), the conclusions are further supported. Finally, relevant policy recommendations for reducing air pollution are proposed based on the empirical results.

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How to Set the Proper CO2 Reduction Targets for the Provincial Building Sector of China?

Sustainability ◽

10.3390/su122410432 ◽

2020 ◽

Vol 12 (24) ◽

pp. 10432

Author(s):

Qingwei Shi ◽

Hong Ren ◽

Weiguang Cai ◽

Jingxin Gao

Keyword(s):

Energy Saving ◽

Co2 Emissions ◽

Carbon Emissions ◽

Emission Reduction ◽

Carbon Emission ◽

National Level ◽

Clean Energy ◽

Energy Structure ◽

Building Sector ◽

Emission Abatement

The improvement of the energy and carbon emission efficiency of activities in the building sector is the key to China’s realization of the Paris Agreement. We can explore effective emission abatement approaches for the building sector by evaluating the carbon emissions and energy efficiency of construction activities, measuring the emission abatement potential of construction activities across the country and regions, and measuring the marginal abatement cost (MAC) of China and various regions. This study calculates the energy and carbon emissions performance of the building sector of 30 provinces and regions in China from 2005 to 2015, measures the dynamic changes in the energy-saving potential and carbon emission performance of the building sector, conducts relevant verification, and estimates the MAC of the building sector by using the slacks-based measure-directional distance function. The level of energy consumption per unit of the building sector of China has been decreasing yearly, but the energy structure has changed minimally (considering that clean energy is used). The total factor technical efficiency of the building sector of various provinces, cities, and regions is generally low, as verified in the evaluation of the energy-saving and emission abatement potential of the building sector of China. The energy saving and emission abatement of the building sector of China have great potential—that is, in approximately 50% of the total emissions of the building sector of China. In particular, Northeast and North China account for more than 50% of the total energy-saving and emission abatement potential. The study of the CO2 emissions and MAC of the building sector indicates that the larger the CO2 emissions are, the smaller MAC will be. The emission abatement efficiency is proportional to MAC. Based on this research, it can be more equitable and effective in formulating provincial emission reduction policy targets at the national level, and can maximize the contribution of the building sector of various provinces to the national carbon emission reduction.

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The Impact of Economy on Carbon Emissions: An Empirical Study Based on the Synergistic Effect of Gender Factors

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph16193723 ◽

2019 ◽

Vol 16 (19) ◽

pp. 3723 ◽

Cited By ~ 1

Author(s):

Shiran Li ◽

Hongbing Deng ◽

Kangkang Zhang

Keyword(s):

Carbon Emissions ◽

Carbon Emission ◽

Negative Impact ◽

Probability Model ◽

National Level ◽

Bayesian Posterior Probability ◽

Model Structure ◽

Surrounding Areas ◽

The Impact ◽

Peripheral Regions

The study of carbon emissions is of great significance for environmental change and economic development. Gender factors is an important perspective to examine the path of carbon emissions. Based on the panel data of 30 provinces in China from 2005 to 2016, this paper selects the optimal spatial measurement model structure by using the Bayesian posterior probability model structure selection method, and studies the impact of economy on carbon emissions and the influence mechanism of gender-based “synergy effect” on carbon emissions from the National level and regional levels. The research shows that the increase of economic promotes the increase of carbon emission in this region, but it has a restraining effect on the carbon emission in the surrounding areas. Moreover, gender factors have a significant positive effect on the region at the National level and the Eastern and Northeastern regions, but not significantly in other ones, and have a significant negative impact on carbon emissions in surrounding areas. Overall, the influence intensity of economy on carbon emission increases with the increase of gender in the National level and the Eastern and Northeastern, while the influence intensity of economy of peripheral regions on carbon emission in Central Region decreases with the increase of gender factors in peripheral regions.

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